10 papers
Reflection Pretraining Enables Token-Level Self-Correction in Biological Sequence Models
Xiang Zhang, Jiaqi Wei, Yuejin Yang +8
Chain-of-Thought (CoT) prompting has significantly advanced task-solving capabilities in natural language processing with large language models. Unlike standard prompting, CoT enco…
Accurate de novo sequencing of the modified proteome with OmniNovo
Yuhan Chen, Shang Qu, Zhiqiang Gao +13
Post-translational modifications (PTMs) serve as a dynamic chemical language regulating protein function, yet current proteomic methods remain blind to a vast portion of the modifi…
Bidirectional Representations Augmented Autoregressive Biological Sequence Generation
Xiang Zhang, Jiaqi Wei, Zijie Qiu +5
Autoregressive (AR) models, common in sequence generation, are limited in many biological tasks such as de novo peptide sequencing and protein modeling by their unidirectional natu…
From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery
Jiaqi Wei, Yuejin Yang, Xiang Zhang +24
Artificial intelligence (AI) is reshaping scientific discovery, evolving from specialized computational tools into autonomous research partners. We position Agentic Science as a pi…
Unifying Tree Search Algorithm and Reward Design for LLM Reasoning: A Survey
Jiaqi Wei, Xiang Zhang, Yuejin Yang +10
Deliberative tree search is a cornerstone of modern Large Language Model (LLM) research, driving the pivot from brute-force scaling toward algorithmic efficiency. This single parad…
Retrieval is Not Enough: Enhancing RAG Reasoning through Test-Time Critique and Optimization
Jiaqi Wei, Hao Zhou, Xiang Zhang +6
Retrieval-augmented generation (RAG) has become a widely adopted paradigm for enabling knowledge-grounded large language models (LLMs). However, standard RAG pipelines often fail t…